SummaryMost celestial bodies, from planets, to stars, to black holes; gain mass during their lives by means of an accretion disc. Understanding the physical processes that determine the rate at which matter accretes and energy is radiated in these discs is vital for unraveling the formation, evolution, and fate of almost every type of object in the Universe. Despite the fact that magnetic fields have been known to be crucial in accretion discs since the early 90’s, the majority of astrophysical questions that depend on the details of how disc accretion proceeds are still being addressed using the “standard” accretion disc model (developed in the early 70’s), where magnetic fields do not play an explicit role. This has prevented us from fully exploring the astrophysical consequences and observational signatures of realistic accretion disc models, leading to a profound disconnect between observations (usually interpreted with the standard paradigm) and modern accretion disc theory and numerical simulations (where magnetic turbulence is crucial). The goal of this proposal is to use several complementary approaches in order to finally move beyond the standard paradigm. This program has two main objectives: 1) Develop the theoretical framework to incorporate magnetic fields, and the ensuing turbulence, into self-consistent accretion disc models, and investigate their observational implications. 2) Investigate transport and radiative processes in collision-less disc regions, where non-thermal radiation originates, by employing a kinetic particle description of the plasma. In order to achieve these goals, we will use, and build upon, state-of-the-art magnetohydrodynamic and particle-in-cell codes in conjunction with theoretical modeling. This framework will make it possible to address fundamental questions on stellar and planet formation, binary systems with a compact object, and supermassive black hole feedback in a way that has no counterpart within the standard paradigm.

Most celestial bodies, from planets, to stars, to black holes; gain mass during their lives by means of an accretion disc. Understanding the physical processes that determine the rate at which matter accretes and energy is radiated in these discs is vital for unraveling the formation, evolution, and fate of almost every type of object in the Universe. Despite the fact that magnetic fields have been known to be crucial in accretion discs since the early 90’s, the majority of astrophysical questions that depend on the details of how disc accretion proceeds are still being addressed using the “standard” accretion disc model (developed in the early 70’s), where magnetic fields do not play an explicit role. This has prevented us from fully exploring the astrophysical consequences and observational signatures of realistic accretion disc models, leading to a profound disconnect between observations (usually interpreted with the standard paradigm) and modern accretion disc theory and numerical simulations (where magnetic turbulence is crucial). The goal of this proposal is to use several complementary approaches in order to finally move beyond the standard paradigm. This program has two main objectives: 1) Develop the theoretical framework to incorporate magnetic fields, and the ensuing turbulence, into self-consistent accretion disc models, and investigate their observational implications. 2) Investigate transport and radiative processes in collision-less disc regions, where non-thermal radiation originates, by employing a kinetic particle description of the plasma. In order to achieve these goals, we will use, and build upon, state-of-the-art magnetohydrodynamic and particle-in-cell codes in conjunction with theoretical modeling. This framework will make it possible to address fundamental questions on stellar and planet formation, binary systems with a compact object, and supermassive black hole feedback in a way that has no counterpart within the standard paradigm.

Max ERC Funding

1 793 697 €

Duration

Start date: 2013-02-01, End date: 2018-01-31

Project acronym3D-PXM

Project3D Piezoresponse X-ray Microscopy

Researcher (PI)Hugh SIMONS

Host Institution (HI)DANMARKS TEKNISKE UNIVERSITET

Call DetailsStarting Grant (StG), PE3, ERC-2018-STG

SummaryPolar materials, such as piezoelectrics and ferroelectrics are essential to our modern life, yet they are mostly developed by trial-and-error. Their properties overwhelmingly depend on the defects within them, the majority of which are hidden in the bulk. The road to better materials is via mapping these defects, but our best tool for it – piezoresponse force microscopy (PFM) – is limited to surfaces. 3D-PXM aims to revolutionize our understanding by measuring the local structure-property correlations around individual defects buried deep in the bulk.
This is a completely new kind of microscopy enabling 3D maps of local strain and polarization (i.e. piezoresponse) with 10 nm resolution in mm-sized samples. It is novel, multi-scale and fast enough to capture defect dynamics in real time. Uniquely, it is a full-field method that uses a synthetic-aperture approach to improve both resolution and recover the image phase. This phase is then quantitatively correlated to local polarization and strain via a forward model. 3D-PXM combines advances in X-Ray optics, phase recovery and data analysis to create something transformative. In principle, it can achieve spatial resolution comparable to the best coherent X-Ray microscopy methods while being faster, used on larger samples, and without risk of radiation damage.
For the first time, this opens the door to solving how defects influence bulk properties under real-life conditions. 3D-PXM focuses on three types of defects prevalent in polar materials: grain boundaries, dislocations and polar nanoregions. Individually they address major gaps in the state-of-the-art, while together making great strides towards fully understanding defects. This understanding is expected to inform a new generation of multi-scale models that can account for a material’s full heterogeneity. These models are the first step towards abandoning our tradition of trial-and-error, and with this comes the potential for a new era of polar materials.

Polar materials, such as piezoelectrics and ferroelectrics are essential to our modern life, yet they are mostly developed by trial-and-error. Their properties overwhelmingly depend on the defects within them, the majority of which are hidden in the bulk. The road to better materials is via mapping these defects, but our best tool for it – piezoresponse force microscopy (PFM) – is limited to surfaces. 3D-PXM aims to revolutionize our understanding by measuring the local structure-property correlations around individual defects buried deep in the bulk.
This is a completely new kind of microscopy enabling 3D maps of local strain and polarization (i.e. piezoresponse) with 10 nm resolution in mm-sized samples. It is novel, multi-scale and fast enough to capture defect dynamics in real time. Uniquely, it is a full-field method that uses a synthetic-aperture approach to improve both resolution and recover the image phase. This phase is then quantitatively correlated to local polarization and strain via a forward model. 3D-PXM combines advances in X-Ray optics, phase recovery and data analysis to create something transformative. In principle, it can achieve spatial resolution comparable to the best coherent X-Ray microscopy methods while being faster, used on larger samples, and without risk of radiation damage.
For the first time, this opens the door to solving how defects influence bulk properties under real-life conditions. 3D-PXM focuses on three types of defects prevalent in polar materials: grain boundaries, dislocations and polar nanoregions. Individually they address major gaps in the state-of-the-art, while together making great strides towards fully understanding defects. This understanding is expected to inform a new generation of multi-scale models that can account for a material’s full heterogeneity. These models are the first step towards abandoning our tradition of trial-and-error, and with this comes the potential for a new era of polar materials.

SummaryThis project presents a new concept for the detection, diagnosis and monitoring of cancer biomarker patterns in point-of-care. The device under development will make use of the selectivity of the plastic antibodies as sensing materials and the interference they will play on the normal operation of a photovoltaic cell.
Plastic antibodies will be designed by surface imprinting procedures. Self-assembled monolayer and molecular imprinting techniques will be merged in this process because they allow the self-assembly of nanostructured materials on a “bottom-up” nanofabrication approach. A dye-sensitized solar cell will be used as photovoltaic cell. It includes a liquid interface in the cell circuit, which allows the introduction of the sample (also in liquid phase) without disturbing the normal cell operation. Furthermore, it works well with rather low cost materials and requires mild and easy processing conditions. The cell will be equipped with plasmonic structures to enhance light absorption and cell efficiency.
The device under development will be easily operated by any clinician or patient. It will require ambient light and a regular multimeter. Eye detection will be also tried out.

This project presents a new concept for the detection, diagnosis and monitoring of cancer biomarker patterns in point-of-care. The device under development will make use of the selectivity of the plastic antibodies as sensing materials and the interference they will play on the normal operation of a photovoltaic cell.
Plastic antibodies will be designed by surface imprinting procedures. Self-assembled monolayer and molecular imprinting techniques will be merged in this process because they allow the self-assembly of nanostructured materials on a “bottom-up” nanofabrication approach. A dye-sensitized solar cell will be used as photovoltaic cell. It includes a liquid interface in the cell circuit, which allows the introduction of the sample (also in liquid phase) without disturbing the normal cell operation. Furthermore, it works well with rather low cost materials and requires mild and easy processing conditions. The cell will be equipped with plasmonic structures to enhance light absorption and cell efficiency.
The device under development will be easily operated by any clinician or patient. It will require ambient light and a regular multimeter. Eye detection will be also tried out.

SummaryMucins are a family of high-molecular-weight glycoproteins and a major macromolecular constituent in slimy mucus gels that are covering the surface of internal biological tissues. A primary role of mucus gels in biological systems is known to be the protection and lubrication of underlying epithelial cell surfaces. This is intuitively well appreciated by both science community and the public, and yet detailed lubrication properties of mucins and mucus gels have remained largely unexplored to date. Detailed and systematic understanding of the lubrication mechanism of mucus gels is significant from many angles; firstly, lubricity of mucus gels is closely related with fundamental functions of various human organs, such as eye blinking, mastication in oral cavity, swallowing through esophagus, digestion in stomach, breathing through air way and respiratory organs, and thus often indicates the health state of those organs. Furthermore, for the application of various tissue-contacting devices or personal care products, e.g. catheters, endoscopes, and contact lenses, mucus gel layer is the first counter surface that comes into the mechanical and tribological contacts with them. Finally, remarkable lubricating performance by mucins and mucus gels in biological systems may provide many useful and possibly innovative hints in utilizing water as base lubricant for man-made engineering systems. This project thus proposes to carry out a 5 year research program focusing on exploring the lubricity of mucins and mucus gels by combining a broad range of experimental approaches in biology and tribology.

Mucins are a family of high-molecular-weight glycoproteins and a major macromolecular constituent in slimy mucus gels that are covering the surface of internal biological tissues. A primary role of mucus gels in biological systems is known to be the protection and lubrication of underlying epithelial cell surfaces. This is intuitively well appreciated by both science community and the public, and yet detailed lubrication properties of mucins and mucus gels have remained largely unexplored to date. Detailed and systematic understanding of the lubrication mechanism of mucus gels is significant from many angles; firstly, lubricity of mucus gels is closely related with fundamental functions of various human organs, such as eye blinking, mastication in oral cavity, swallowing through esophagus, digestion in stomach, breathing through air way and respiratory organs, and thus often indicates the health state of those organs. Furthermore, for the application of various tissue-contacting devices or personal care products, e.g. catheters, endoscopes, and contact lenses, mucus gel layer is the first counter surface that comes into the mechanical and tribological contacts with them. Finally, remarkable lubricating performance by mucins and mucus gels in biological systems may provide many useful and possibly innovative hints in utilizing water as base lubricant for man-made engineering systems. This project thus proposes to carry out a 5 year research program focusing on exploring the lubricity of mucins and mucus gels by combining a broad range of experimental approaches in biology and tribology.

Max ERC Funding

1 432 920 €

Duration

Start date: 2011-04-01, End date: 2016-03-31

Project acronym5HTCircuits

ProjectModulation of cortical circuits and predictive neural coding by serotonin

SummarySerotonin (5-HT) is a central neuromodulator and a major target of therapeutic psychoactive drugs, but relatively little is known about how it modulates information processing in neural circuits. The theory of predictive coding postulates that the brain combines raw bottom-up sensory information with top-down information from internal models to make perceptual inferences about the world. We hypothesize, based on preliminary data and prior literature, that a role of 5-HT in this process is to report prediction errors and promote the suppression and weakening of erroneous internal models. We propose that it does this by inhibiting top-down relative to bottom-up cortical information flow. To test this hypothesis, we propose a set of experiments in mice performing olfactory perceptual tasks. Our specific aims are: (1) We will test whether 5-HT neurons encode sensory prediction errors. (2) We will test their causal role in using predictive cues to guide perceptual decisions. (3) We will characterize how 5-HT influences the encoding of sensory information by neuronal populations in the olfactory cortex and identify the underlying circuitry. (4) Finally, we will map the effects of 5-HT across the whole brain and use this information to target further causal manipulations to specific 5-HT projections. We accomplish these aims using state-of-the-art optogenetic, electrophysiological and imaging techniques (including 9.4T small-animal functional magnetic resonance imaging) as well as psychophysical tasks amenable to quantitative analysis and computational theory. Together, these experiments will tackle multiple facets of an important general computational question, bringing to bear an array of cutting-edge technologies to address with unprecedented mechanistic detail how 5-HT impacts neural coding and perceptual decision-making.

Serotonin (5-HT) is a central neuromodulator and a major target of therapeutic psychoactive drugs, but relatively little is known about how it modulates information processing in neural circuits. The theory of predictive coding postulates that the brain combines raw bottom-up sensory information with top-down information from internal models to make perceptual inferences about the world. We hypothesize, based on preliminary data and prior literature, that a role of 5-HT in this process is to report prediction errors and promote the suppression and weakening of erroneous internal models. We propose that it does this by inhibiting top-down relative to bottom-up cortical information flow. To test this hypothesis, we propose a set of experiments in mice performing olfactory perceptual tasks. Our specific aims are: (1) We will test whether 5-HT neurons encode sensory prediction errors. (2) We will test their causal role in using predictive cues to guide perceptual decisions. (3) We will characterize how 5-HT influences the encoding of sensory information by neuronal populations in the olfactory cortex and identify the underlying circuitry. (4) Finally, we will map the effects of 5-HT across the whole brain and use this information to target further causal manipulations to specific 5-HT projections. We accomplish these aims using state-of-the-art optogenetic, electrophysiological and imaging techniques (including 9.4T small-animal functional magnetic resonance imaging) as well as psychophysical tasks amenable to quantitative analysis and computational theory. Together, these experiments will tackle multiple facets of an important general computational question, bringing to bear an array of cutting-edge technologies to address with unprecedented mechanistic detail how 5-HT impacts neural coding and perceptual decision-making.

SummaryWhen faced with a threat, an animal must decide whether to freeze, reducing its chances of being noticed, or to flee to the safety of a refuge. Animals from fish to primates choose between these two alternatives when confronted by an attacking predator, a choice that largely depends on the context in which the threat occurs. Recent work has made strides identifying the pre-motor circuits, and their inputs, which control freezing behavior in rodents, but how contextual information is integrated to guide this choice is still far from understood. We recently found that fruit flies in response to visual looming stimuli, simulating a large object on collision course, make rapid freeze/flee choices that depend on the social and spatial environment, and the fly’s internal state. Further, identification of looming detector neurons was recently reported and we identified the descending command neurons, DNp09, responsible for freezing in the fly. Knowing the sensory input and descending output for looming-evoked freezing, two environmental factors that modulate its expression, and using a genetically tractable system affording the use of large sample sizes, places us in an unique position to understand how a information about a threat is integrated with cues from the environment to guide the choice of whether to freeze (our goal). To assess how social information impinges on the circuit for freezing, we will examine the sensory inputs and neuromodulators that mediate this process, mapping their connections to DNp09 neurons (Aim 1). We ask whether learning is required for the spatial modulation of freezing, which cues flies are using to discriminate different places and which brain circuits mediate this process (Aim 2). Finally, we will study how activity of DNp09 neurons drives freezing (Aim 3). This project will provide a comprehensive understanding of the mechanism of freezing and its modulation by the environment, from single neurons to behaviour.

When faced with a threat, an animal must decide whether to freeze, reducing its chances of being noticed, or to flee to the safety of a refuge. Animals from fish to primates choose between these two alternatives when confronted by an attacking predator, a choice that largely depends on the context in which the threat occurs. Recent work has made strides identifying the pre-motor circuits, and their inputs, which control freezing behavior in rodents, but how contextual information is integrated to guide this choice is still far from understood. We recently found that fruit flies in response to visual looming stimuli, simulating a large object on collision course, make rapid freeze/flee choices that depend on the social and spatial environment, and the fly’s internal state. Further, identification of looming detector neurons was recently reported and we identified the descending command neurons, DNp09, responsible for freezing in the fly. Knowing the sensory input and descending output for looming-evoked freezing, two environmental factors that modulate its expression, and using a genetically tractable system affording the use of large sample sizes, places us in an unique position to understand how a information about a threat is integrated with cues from the environment to guide the choice of whether to freeze (our goal). To assess how social information impinges on the circuit for freezing, we will examine the sensory inputs and neuromodulators that mediate this process, mapping their connections to DNp09 neurons (Aim 1). We ask whether learning is required for the spatial modulation of freezing, which cues flies are using to discriminate different places and which brain circuits mediate this process (Aim 2). Finally, we will study how activity of DNp09 neurons drives freezing (Aim 3). This project will provide a comprehensive understanding of the mechanism of freezing and its modulation by the environment, from single neurons to behaviour.

Max ERC Funding

1 969 750 €

Duration

Start date: 2019-02-01, End date: 2024-01-31

Project acronymaCROBAT

ProjectCircadian Regulation Of Brown Adipose Thermogenesis

Researcher (PI)Zachary Philip Gerhart-Hines

Host Institution (HI)KOBENHAVNS UNIVERSITET

Call DetailsStarting Grant (StG), LS4, ERC-2014-STG

SummaryObesity and diabetes have reached pandemic proportions and new therapeutic strategies are critically needed. Brown adipose tissue (BAT), a major source of heat production, possesses significant energy-dissipating capacity and therefore represents a promising target to use in combating these diseases. Recently, I discovered a novel link between circadian rhythm and thermogenic stress in the control of the conserved, calorie-burning functions of BAT. Circadian and thermogenic signaling to BAT incorporates blood-borne hormonal and nutrient cues with direct neuronal input. Yet how these responses coordinately shape BAT energy-expending potential through the regulation of cell surface receptors, metabolic enzymes, and transcriptional effectors is still not understood. My primary goal is to investigate this previously unappreciated network of crosstalk that allows mammals to effectively orchestrate daily rhythms in BAT metabolism, while maintaining their ability to adapt to abrupt changes in energy demand. My group will address this question using gain and loss-of-function in vitro and in vivo studies, newly-generated mouse models, customized physiological phenotyping, and cutting-edge advances in next generation RNA sequencing and mass spectrometry. Preliminary, small-scale validations of our methodologies have already yielded a number of novel candidates that may drive key facets of BAT metabolism. Additionally, we will extend our circadian and thermogenic studies into humans to evaluate the translational potential. Our results will advance the fundamental understanding of how daily oscillations in bioenergetic networks establish a framework for the anticipation of and adaptation to environmental challenges. Importantly, we expect that these mechanistic insights will reveal pharmacological targets through which we can unlock evolutionary constraints and harness the energy-expending potential of BAT for the prevention and treatment of obesity and diabetes.

Obesity and diabetes have reached pandemic proportions and new therapeutic strategies are critically needed. Brown adipose tissue (BAT), a major source of heat production, possesses significant energy-dissipating capacity and therefore represents a promising target to use in combating these diseases. Recently, I discovered a novel link between circadian rhythm and thermogenic stress in the control of the conserved, calorie-burning functions of BAT. Circadian and thermogenic signaling to BAT incorporates blood-borne hormonal and nutrient cues with direct neuronal input. Yet how these responses coordinately shape BAT energy-expending potential through the regulation of cell surface receptors, metabolic enzymes, and transcriptional effectors is still not understood. My primary goal is to investigate this previously unappreciated network of crosstalk that allows mammals to effectively orchestrate daily rhythms in BAT metabolism, while maintaining their ability to adapt to abrupt changes in energy demand. My group will address this question using gain and loss-of-function in vitro and in vivo studies, newly-generated mouse models, customized physiological phenotyping, and cutting-edge advances in next generation RNA sequencing and mass spectrometry. Preliminary, small-scale validations of our methodologies have already yielded a number of novel candidates that may drive key facets of BAT metabolism. Additionally, we will extend our circadian and thermogenic studies into humans to evaluate the translational potential. Our results will advance the fundamental understanding of how daily oscillations in bioenergetic networks establish a framework for the anticipation of and adaptation to environmental challenges. Importantly, we expect that these mechanistic insights will reveal pharmacological targets through which we can unlock evolutionary constraints and harness the energy-expending potential of BAT for the prevention and treatment of obesity and diabetes.

SummaryThe brain evolves, develops, and operates in the context of animal movements. As a consequence, fundamental brain functions such as spatial perception and motor control critically depend on the precise knowledge of the ongoing body motion. An accurate internal estimate of self-movement is thought to emerge from sensorimotor integration; nonetheless, which circuits perform this internal estimation, and exactly how motor-sensory coordination is implemented within these circuits are basic questions that remain to be poorly understood. There is growing evidence suggesting that, during locomotion, motor-related and visual signals interact at early stages of visual processing. In mammals, however, it is not clear what the function of this interaction is. Recently, we have shown that a population of Drosophila optic-flow processing neurons —neurons that are sensitive to self-generated visual flow, receives convergent visual and walking-related signals to form a faithful representation of the fly’s walking movements. Leveraging from these results, and combining quantitative analysis of behavior with physiology, optogenetics, and modelling, we propose to investigate circuit mechanisms of self-movement estimation during walking. We will:1) use cell specific manipulations to identify what cells are necessary to generate the motor-related activity in the population of visual neurons, 2) record from the identified neurons and correlate their activity with specific locomotor parameters, and 3) perturb the activity of different cell-types within the identified circuits to test their role in the dynamics of the visual neurons, and on the fly’s walking behavior. These experiments will establish unprecedented causal relationships among neural activity, the formation of an internal representation, and locomotor control. The identified sensorimotor principles will establish a framework that can be tested in other scenarios or animal systems with implications both in health and disease.

The brain evolves, develops, and operates in the context of animal movements. As a consequence, fundamental brain functions such as spatial perception and motor control critically depend on the precise knowledge of the ongoing body motion. An accurate internal estimate of self-movement is thought to emerge from sensorimotor integration; nonetheless, which circuits perform this internal estimation, and exactly how motor-sensory coordination is implemented within these circuits are basic questions that remain to be poorly understood. There is growing evidence suggesting that, during locomotion, motor-related and visual signals interact at early stages of visual processing. In mammals, however, it is not clear what the function of this interaction is. Recently, we have shown that a population of Drosophila optic-flow processing neurons —neurons that are sensitive to self-generated visual flow, receives convergent visual and walking-related signals to form a faithful representation of the fly’s walking movements. Leveraging from these results, and combining quantitative analysis of behavior with physiology, optogenetics, and modelling, we propose to investigate circuit mechanisms of self-movement estimation during walking. We will:1) use cell specific manipulations to identify what cells are necessary to generate the motor-related activity in the population of visual neurons, 2) record from the identified neurons and correlate their activity with specific locomotor parameters, and 3) perturb the activity of different cell-types within the identified circuits to test their role in the dynamics of the visual neurons, and on the fly’s walking behavior. These experiments will establish unprecedented causal relationships among neural activity, the formation of an internal representation, and locomotor control. The identified sensorimotor principles will establish a framework that can be tested in other scenarios or animal systems with implications both in health and disease.

Max ERC Funding

1 500 000 €

Duration

Start date: 2017-11-01, End date: 2022-10-31

Project acronymADAPT

ProjectOrigins and factors governing adaptation: Insights from experimental evolution and population genomic data

Researcher (PI)Thomas, Martin Jean Bataillon

Host Institution (HI)AARHUS UNIVERSITET

Call DetailsStarting Grant (StG), LS8, ERC-2012-StG_20111109

Summary"I propose a systematic study of the type of genetic variation enabling adaptation and factors that limit rates of adaptation in natural populations. New methods will be developed for analysing data from experimental evolution and population genomics. The methods will be applied to state of the art data from both fields. Adaptation is generated by natural selection sieving through heritable variation. Examples of adaptation are available from the fossil record and from extant populations. Genomic studies have supplied many instances of genomic regions exhibiting footprint of natural selection favouring new variants. Despite ample proof that adaptation happens, we know little about beneficial mutations– the raw stuff enabling adaptation. Is adaptation mediated by genetic variation pre-existing in the population, or by variation supplied de novo through mutations? We know even less about what factors limit rates of adaptation. Answers to these questions are crucial for Evolutionary Biology, but also for believable quantifications of the evolutionary potential of populations. Population genetic theory makes predictions and allows inference from the patterns of polymorphism within species and divergence between species. Yet models specifying the fitness effects of mutations are often missing. Fitness landscape models will be mobilized to fill this gap and develop methods for inferring the distribution of fitness effects and factors governing rates of adaptation. Insights into the processes underlying adaptation will thus be gained from experimental evolution and population genomics data. The applicability of insights gained from experimental evolution to comprehend adaptation in nature will be scrutinized. We will unite two very different approaches for studying adaptation. The project will boost our understanding of how selection shapes genomes and open the way for further quantitative tests of theories of adaptation."

"I propose a systematic study of the type of genetic variation enabling adaptation and factors that limit rates of adaptation in natural populations. New methods will be developed for analysing data from experimental evolution and population genomics. The methods will be applied to state of the art data from both fields. Adaptation is generated by natural selection sieving through heritable variation. Examples of adaptation are available from the fossil record and from extant populations. Genomic studies have supplied many instances of genomic regions exhibiting footprint of natural selection favouring new variants. Despite ample proof that adaptation happens, we know little about beneficial mutations– the raw stuff enabling adaptation. Is adaptation mediated by genetic variation pre-existing in the population, or by variation supplied de novo through mutations? We know even less about what factors limit rates of adaptation. Answers to these questions are crucial for Evolutionary Biology, but also for believable quantifications of the evolutionary potential of populations. Population genetic theory makes predictions and allows inference from the patterns of polymorphism within species and divergence between species. Yet models specifying the fitness effects of mutations are often missing. Fitness landscape models will be mobilized to fill this gap and develop methods for inferring the distribution of fitness effects and factors governing rates of adaptation. Insights into the processes underlying adaptation will thus be gained from experimental evolution and population genomics data. The applicability of insights gained from experimental evolution to comprehend adaptation in nature will be scrutinized. We will unite two very different approaches for studying adaptation. The project will boost our understanding of how selection shapes genomes and open the way for further quantitative tests of theories of adaptation."

Summary"Understanding the dawn of the first galaxies and how their light permeated the early Universe is at the very frontier of modern astrophysical cosmology. Generous resources, including ambitions observational programs, are being devoted to studying these epochs of Cosmic Dawn (CD) and Reionization (EoR). In order to interpret these observations, we propose to build on our widely-used, semi-numeric simulation tool, 21cmFAST, and apply it to observations. Using sub-grid, semi-analytic models, we will incorporate additional physical processes governing the evolution of sources and sinks of ionizing photons. The resulting state-of-the-art simulations will be well poised to interpret topical observations of quasar spectra and the cosmic 21cm signal. They would be both physically-motivated and fast, allowing us to rapidly explore astrophysical parameter space. We will statistically quantify the resulting degeneracies and constraints, providing a robust answer to the question, ""What can we learn from EoR/CD observations?"" As an end goal, these investigations will help us understand when the first generations of galaxies formed, how they drove the EoR, and what are the associated large-scale observational signatures."

"Understanding the dawn of the first galaxies and how their light permeated the early Universe is at the very frontier of modern astrophysical cosmology. Generous resources, including ambitions observational programs, are being devoted to studying these epochs of Cosmic Dawn (CD) and Reionization (EoR). In order to interpret these observations, we propose to build on our widely-used, semi-numeric simulation tool, 21cmFAST, and apply it to observations. Using sub-grid, semi-analytic models, we will incorporate additional physical processes governing the evolution of sources and sinks of ionizing photons. The resulting state-of-the-art simulations will be well poised to interpret topical observations of quasar spectra and the cosmic 21cm signal. They would be both physically-motivated and fast, allowing us to rapidly explore astrophysical parameter space. We will statistically quantify the resulting degeneracies and constraints, providing a robust answer to the question, ""What can we learn from EoR/CD observations?"" As an end goal, these investigations will help us understand when the first generations of galaxies formed, how they drove the EoR, and what are the associated large-scale observational signatures."